We present three extensions to a base optimization model for a transit line which can be used to strategically evaluate technology choices. We add to the base model optimal stop spacing and train length, a crowding penalty, and a multi-period generalization. These extensions are analytically solvable by simple approximations and lead to meaningful insights. Their significance is illustrated by means of an example in which two road modes and two rail modes are defined by a set of techno-economical parameters. These parameters loaded in the base model yield dominance of road modes for all but the largest demand levels. We consistently keep this set of parameters for all models, and show how the break-even points between road and rail modes progressively recede toward lower demand levels when model refinements - not parameter changes - are applied. Scenario analyses of plausible parameter sets highlight the model's versatility, and caution on general conclusions regarding technology dominance.

Improved models for technology choice in a transit corridor with fixed demand

Moccia Luigi;
2016

Abstract

We present three extensions to a base optimization model for a transit line which can be used to strategically evaluate technology choices. We add to the base model optimal stop spacing and train length, a crowding penalty, and a multi-period generalization. These extensions are analytically solvable by simple approximations and lead to meaningful insights. Their significance is illustrated by means of an example in which two road modes and two rail modes are defined by a set of techno-economical parameters. These parameters loaded in the base model yield dominance of road modes for all but the largest demand levels. We consistently keep this set of parameters for all models, and show how the break-even points between road and rail modes progressively recede toward lower demand levels when model refinements - not parameter changes - are applied. Scenario analyses of plausible parameter sets highlight the model's versatility, and caution on general conclusions regarding technology dominance.
2016
Istituto di Calcolo e Reti ad Alte Prestazioni - ICAR
Bus rapid transit
Commuter rail
Light rail transit
Transit optimization
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/310528
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